The present invention relates to diagnostic ultrasound systems which measure and image anatomical structures, and their movement. More particularly, the present invention relates to a signal processing method and apparatus for calculation and display of tissue deformation to be used in ultrasonic imaging systems.
Recently, within the field of ultrasound imaging, physicians have become interested in using tissue deformation properties, such as tissue strain and strain velocity for clinical measurements.
The term “strain” refers to a characteristic of material being examined. For example, the strain associated with muscle tissue corresponds to a ratio of the change in muscle tissue length during a prescribed time interval to the muscle tissue's initial length. In ultrasound imaging, the rate of change of strain (e.g., strain rate, strain velocity, etc.) may be visually presented to a physician as a colorized 2-dimensional image, where variations in color correspond to different strain velocities. It has become apparent that the viability of a segment of the muscle is related to the amount of muscle strain and temporal behavior of the strain that is performed by, or is imposed on the muscle segment. Also, it has been determined that malignant tumors may be detected based on their resistance to compression.
One application of real-time strain velocity imaging is in cardiology. The strain velocity gives a direct and quantitative measure for the ability of the myocardium to contract and relax. By imaging along the myocard from an apical view, the local strain velocity component along the long axis of the heart can be measured. Measuring the local strain velocity component gives information about the local shortening and lengthening of the heart wall. By imaging from the parasternal view, the strain velocity component perpendicular to the heart wall can be found. Finding the strain velocity component perpendicular to the heart wall gives information about the local thickening of the muscle. Wall thickening measured with M-mode or from the 2D image is a commonly used measure for muscle viability. With strain velocity imaging, a direct measure for this thickening is available. The strain velocity images can potentially add to the diagnosis of a number of cardiac disorders.
Another application of strain velocity imaging is in heart transplants. Velocity variations inside the myocardium are important for the diagnosis of rejection after heart transplantation. The strain velocity images give a direct display of these velocity variations.
Another application of strain velocity imaging is in noninvasive electrophysiology. The preferred embodiment describes techniques to image the local contraction/relaxation contributions with a high spatial and temporal resolution. Local contraction/relaxation information can be used to accurately determine the localization of, for example, where the mechanical movement in the heart chambers is activated based on a cross section just below the AV-plane. Furthermore, aberrant conduction pathways (Wolf-Parkinson-White) from the atrium to the ventricle can be localized for later ablation. Even the depth inside myocard of these paths can be better localized with this invention in order to determine if the patient should be treated with catheter techniques or surgical techniques.
Another application of strain velocity imaging is in measuring cardiac wall thickening. A well established methodology in cardiac diagnosis is to acquire a M-Mode image and to measure the wall thickening of myocardium during systole. The preferred embodiment provides techniques to take this wall thickening information and measure it in real-time with a high precision in both the spatial and temporal domain. The high diagnostic relevance of the current wall thickening measurements indicates that the imaging modality described in this invention contains highly relevant information for cardiac diagnosis
To understand strain velocity or strain rate in more detail, it is assumed that an object of initial length L0 may be stretched or compressed or itself lengthens or contracts to a different length L. The one-dimensional strain, defined as
                    ɛ        =                              L            -                          L              0                                            L            0                                              (        1        )            represents a dimensionless description of the change. If the length L is considered to be a function of time, the temporal derivative of the strain, the strain velocity, can be found using
                              ɛ          •                =                              ∂            ɛ                                ∂            t                                              (        2        )            
If the velocity, ν of every point in the object is known, an equivalent definition of the strain velocity is:
                              ɛ          •                =                              ∂            v                                ∂            r                                              (        3        )            
These equations also provide a useful description of the deformation of the object. In Eq. 3, r is the spatial direction of the stretching or compression. The relation between Eq. 2 and Eq. 3 can be seen if the length L is defined as L(t)=r2(t)−r1(t), and L0=L(t0), where r1 is the distance to one end of the object, and r2 is the distance to the other, and letting t→t0, and letting r1→r2. As illustrated in Eq. 3, the strain velocity is in fact the spatial gradient of the velocity. The strain velocity thus measures the rate of the deformation of the object. If the strain velocity is zero, the shape of the object is not changing. If the strain velocity is positive, the length of the object is increasing, and if the strain velocity is negative, the length of the object is decreasing. Strain velocity is also known as rate-of-deformation, stretching, strain rate or velocity strain.
Strain imaging is currently an established research area in ultrasonic imaging. The degree of deformation in imaged structure may be estimated by correlation of 2D images obtained before and after a pressure increase. One disadvantage of estimating image deformation based on correlation of images is that the instantaneous value of the strain is not calculated nor displayed in real-time. The lack of a real-time capability is an important clinical disadvantage. For example, if strain imaging could be performed in real-time, strain imaging could be applied more effectively in cardiac ultrasound or could be used as an interactive inspection modality where anomalies in tissue compressibility can be visualized in real-time according to the pressure gradients that are applied to the imaged structures.
A method of position tracking has been proposed to estimate the local myocardial strain velocity based on radio frequency (RF) M-Mode acquisitions. The position tracking method is described in H. Kanai, H. Hasegawa, N. Chubachi, Y. Koiwa, and M. Tanaka, “Noninvasive evaluation of local myocardial thickening and its color-coded imaging,” IEEE Trans. on Ultrasonics, Ferroelectrics and Frequency Control, vol. 44, pp. 752-768, 1997. However, the method described in the Kanai et al. article has the disadvantages of poor temporal resolution and high computational cost, which render real-time imaging difficult and costly. Furthermore, the method described in the Kanai et al. article is a manual M-mode technique, not well suited to form the basis for real-time two-dimensional strain images. Also, the strain velocity is a derivative of a velocity estimate and is therefore very noise sensitive. The fundamental velocity aliasing problem that is inherent in tissue velocity imaging makes noise difficult to overcome because aliasing prevents the pulse repetition frequency from being set at a low enough rate to allow a large observation time. If the observation time could be increased, the noise robustness of the strain velocity images could be significantly improved.
Certain of the above identified difficulties are addressed and overcome according to the teachings of U.S. patent application Ser. No. 09/167,896, filed Oct. 7, 1998 and entitled “A METHOD AND APPARATUS FOR PROVIDING REAL-TIME CALCULATION AND DISPLAY OF STRAIN IN ULTRASOUND IMAGING,” which is incorporated herein by reference. However, is an object of the present invention to supplement and/or improve upon such teachings. Certain additional difficulties and shortcomings of the prior art are described below.
To achieve high frame rate in color Doppler applications, two previously known techniques are commonly used: multi line acquisition (MLA) and interleaving. These techniques make it possible to acquire more data than in a basic mode, where the scanner after one pulse is received waits the specified pulse repetition time (T) before firing the next pulse in the same direction. The time to acquire a frame of Doppler data in the basic mode is:tD0=NbNT,  (4)where N is the number of pulses in each direction and Nb is the number of beams in the image. A relatively small extra delay related to the change in setup of the transmitter and beamformer is ignored to simplify the discussion.
In the MLA method, a broad beam is transmitted. When receiving the echo, the signals from all the transducer elements are processed in parallel in two or more beamformers. Each beamformer time delays the element signals differently to generate different receive beams. This way, two or more beams can be acquired during the time for one pulse-echo cycle, and the frame rate can be increased correspondingly. Using MLA, the time to acquire a frame of Doppler data is
                                          t            DMLA                    =                                                    N                b                                            N                MLA                                      ⁢            NT                          ,                            (        5        )            where NMLA is the number of beams that are processed in parallel.
In the interleaving technique, the waiting time T from one pulse to the next in the same direction is utilized to send pulses in other directions, as illustrated in FIG. 1. There is however a minimum waiting time T0 where no other pulses can be fired in any direction. This is given by the time for the pulse to travel to the maximum depth and back: T0>2d/c. The number of directions that pulses are fired during the time T is called the interleave group size, Nint. This obviously has to be an integer number, and T=NintT0. Using interleaving, the time to acquire a frame of Doppler data becomes:
                              t                      D            ⁢                                                  ⁢            int                          =                                            N              b                                                      N                int                            ⁢                              N                MLA                                              ⁢                      NT            .                                              (        6        )            
FIG. 1 illustrates the pulse order and beam directions in the interleaving method for three different interleave group sizes Nint. The number of beams, Nb, equals 8 and packet size, N, equals 2 in the example of FIG. 1. For interleave pattern 100, the interleave group size, Nint, equals 8, for interleave pattern 110, Nint, equals 4 and for interleave pattern 120, Nint equals 1.
A typical scanning procedure for a tissue Doppler application is illustrated in FIG. 2. In the example of FIG. 2, the packet size N equals 3 and the interleave group size Nint equals Nb. T is the pulse repetition time, tT and tD are the times needed to acquire a tissue frame and a Doppler frame respectively, and tF is the total acquisition time for one tissue Doppler frame. A tissue frame 130 is first captured, using high beam density. The PRF used for tissue Doppler is usually so low that only one interleave group is necessary. So N Doppler subframes 132, 134 and 136 are captured separately, usually using fewer beams than in the tissue frame. The velocity is calculated from the N subframes 132, 134 and 136, color coded and then mapped onto the tissue frame. The time to acquire a tissue Doppler frame then becomes:
                                          t            F                    =                                    t              T                        +                                                            N                  b                                                  N                  MLA                                            ⁢              NT                                      ,                            (        7        )            where tT is the time required to acquire the tissue frame. It is, thus, apparent that the maximum frame rate is limited by the above described ultrasound data acquisition schemes.
It is known that tissue velocity can be estimated using either the first or the second harmonic component of the ultrasound signal. Using the second harmonic component (octave imaging) has been reported to produce an improvement in image quality in gray scale images, and the same improvement can be expected in tissue Doppler. There is however a disadvantage in that the Nyquist limit is halved when using the second harmonic instead of the fundamental component. Using a low PRF is also preferable, since the phase amplitude of the complex signal is increased compared to the noise, resulting in a lower variance in the velocity estimate. A disadvantage of using a low PRF is that the Nyquist limit is further reduced. A reduced Nyquist limit increases the risk of aliasing, which results in the misrepresentation of high velocities.